Sequential Source Coding for Stochastic Systems Subject to Finite Rate Constraints

In this article, we revisit the sequential source-coding framework to analyze fundamental performance limitations of discrete-time stochastic control systems subject feedback data-rate constraints in finite-time horizon. The basis our results is a new characterization lower bound on minimum total-rate achieved by codes total (across time) distortion constraint and computational algorithm that allocates optimally rate-distortion, for given level, at each instant time any fixed idea behind facilitates derivation analytical , xmlns:xlink="http://www.w3.org/1999/xlink">nonasymptotic xmlns:xlink="http://www.w3.org/1999/xlink">finite-dimensional upper bounds two control-related scenarios: a) A parallel time-varying Gauss–Markov process with identically distributed spatial components are quantized transmitted through noiseless channel mean-squared error decoder; b) linear quadratic Gaussian (LQG) closed-loop system, random allocation. Our nonasymptotic LQG problem reveals absolute data-rates (mean square) stability plant We supplement illustrative simulation experiments.